The weight of breads prepared in a baker is randomly distributed with a mean of 400 grams and standarddeviation of 16 grams. Using an independently selected sample of 16 breads,finda) the mean and standard deviation of the average weight of these 16 samples.b) using central limit theorem, estimate the probability that the average weight of samples is less than390. The weight of breads prepared in a baker is randomly distributed with a mean of 400 grams and standarddeviation of 16 grams. Using an independently selected sample of 16 breads,finda) the mean and standard deviation of the average weight of these 16 samples.b) using central limit theorem, estimate the probability that the average weight of samples is less than390.

Given that, μ=400,σ=16,n=16 (a) The mean and standard deviation of the average weight of these 16…

Answered: he weight of breads prepared in a baker…

Algebra & Trigonometry with Analytic Geometry

13th Edition

ISBN:9781133382119

Author:Swokowski

Publisher:Swokowski

Chapter10: Sequences, Series, And Probability

Section: Chapter Questions

Problem 27T

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The weight of breads prepared in a baker is randomly distributed with a mean of 400 grams and standard
deviation of 16 grams. Using an independently selected sample of 16 breads,
find
a) the mean and standard deviation of the average weight of these 16 samples.
b) using central limit theorem, estimate the probability that the average weight of samples is less than
390.

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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